102 A two-centre survey of caregiver perspectives on opioid use for children’s acute pain management
Bibliographic record
Abstract
Given the current opioid crisis, caregivers have mounting fears regarding the use of opioid medication in their children. Since caregivers are often the gatekeepers to their children’s pain management, understanding their perspectives on analgesics is essential. For caregivers of children with acute injury presenting to the pediatric emergency department (PED), we aimed to determine caregivers’: a) willingness to accept opioids from emergency care providers, b) reasons for refusing opioids, and c) past experiences with opioids. A novel 31-item electronic survey was offered, via tablet device, to caregivers of children aged 4–16 years who had a musculoskeletal injury <7 days old and presented to one of two Canadian PEDs between March and November 2017. Primary outcome was caregiver willingness to accept opioids for moderate pain for their children. 517 caregivers completed the survey. The mean caregiver age was 40.9 +/- 7 years with 70.0% (362/517) being mothers. 15% (76/506) reported personal or family member diagnosis of a substance use disorder. Children included 62.2% (321/516) males with an overall mean age of 10 +/- 3.6 years. 49.6% of caregivers (254/512) reported willingness to accept opioids for moderate pain that persisted after adequate dosing of non-opioid analgesia, while 37.1% (190/512) were unsure what they would do. Only 33.2% (170/512) of caregivers stated they would accept opioid analgesia upon discharge while 45.5% (233/512) were unsure about at-home use. Caregivers were primarily concerned about side effects, overdose, addiction, and masking of diagnosis. Caregiver fear of addiction (OR 1.12, 95% CI 1.01–1.25) and side effects (OR 1.25, 95% CI 1.11–1.42) increased the odds of rejecting opioids in the emergency department, while fears of addiction (OR 1.19, 95% CI 1.07–1.32) and overdose (OR 1.15, 95% CI 1.04–1.27) increased the odds of rejecting opioids for at-home use. Only half of caregivers reported that they would accept opioids for moderate pain, despite ongoing pain following non-opioid analgesics. Caregiver fears of addiction, side effects, overdose, and masking their child’s diagnosis influence their behaviours. These findings are a first step in understanding caregiver decision-making and can guide healthcare providers in their conversations about acute pain treatment with families.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".